For banks, NBFCs, MFIs and fintechs

Add area affordability to how you source and size.

Sourcing teams spend the same effort in every pincode, whether or not it can carry the product. PaisaMaps ranks pincodes by income, spend and banking depth, so effort and limits follow the market.

Talk to us Open the free map

Banks & NBFCsMFIsFintech & BNPL

15,341: pincodes with income and spend estimates
5: banking and tax signals, each with its level
Area: level only: the same for everyone in a pincode
CSV · API: join it to your book on pincode

Use it the right way

An area input, not a credit score

Good for

Prioritising where to source
Sizing a product by region
An area feature next to your own customer data
Branch and agent planning

Not for

Approving or declining an individual
Replacing bureau data or your model governance
Anything that needs household-level income

What you can achieve

Put sourcing effort where the market is

ObjectivePrioritise sourcing by area

With PaisaMapsRank pincodes by estimated income and spend, and see how banked they already are.

OutcomeField teams and campaigns pointed at pincodes that can carry the product.

ObjectiveSize a new product by region

With PaisaMapsExport households, income and spend by pincode for any region.

OutcomeA market-size estimate you can build a business plan on.

ObjectiveFind under-served markets

With PaisaMapsSwitch between purchasing power and branch density to spot strong spending with thin banking.

OutcomeA list of pincodes where demand is ahead of supply.

ObjectiveAdd an area feature to your models

With PaisaMapsPull signals by pincode with an API key and join them to your book.

OutcomeAn extra, documented input next to your bureau and customer data.

ObjectivePlan branches and agents

With PaisaMapsOverlay your existing branches or customers and read each against its area.

OutcomeCoverage gaps and over-served areas, side by side.

Who's involved

Who uses it, who reads it, who pays for it

Uses it every week

Credit risk / analytics analyst
Growth or sourcing manager
Data scientist

Exports signals by pincode, joins them to the book, ranks areas for sourcing.

What they getA documented area feature and a sourcing priority list.

Reads and decides

Head of risk
Head of retail lending
Product head
Branch expansion committee

Approves where to source, which regions to launch in, which features enter the model.

What they getArea-level evidence with a clear source for model review.

Pays for it

Chief risk officer
Head of growth / distribution
CTO (for API use)

Owns the analytics, data or distribution budget.

What they getSourcing spend and branches pointed at areas that can carry the product.

A business case, start to finish

An NBFC chooses districts for a two-wheeler loan launch

Illustrative example, not a customer story

Choose the signalsPurchasing power, deposits per person, tax filers and the car-to-two-wheeler mix.
Export by pincodeAll of the state's scored pincodes as CSV, with each signal's level.
Join to the bookMatch on pincode against existing customers and branches in the NBFC's own system.
Rank and phasePhase 1 goes to pincodes with spending power, banking depth and two-wheeler-led mobility.

The decision

Sourcing starts in the top-ranked pincodes; the area signals are added as features in the NBFC's own model, reviewed under its governance.

What the team walks away with

A pincode list for phase 1, with the reasons
An area-feature file joined on pincode
An API key to refresh it as the data updates

Signals that matter here

Which signal answers which question

Every plan sees purchasing power, income and spend. These are the signal groups that move this decision.

Signal group	What it tells you	The decision it feeds
Purchasing power	How much a typical household earns and spends, and how that ranks in its state	Where your price point has enough customers; which sites to shortlist
Banking & UPI	How banked and how digitally active an area is	Where credit, payments or premium products will be adopted first
Tax & economy	How many people file income tax, and the local business base	Formal-income depth for lending; B2B and SME demand
Vehicles	Car ownership, the car-to-two-wheeler mix, luxury and EV share	Premium vs value positioning; parking-led formats; mobility products

Each signal's source and level (pincode, district or state) is listed on the signals page.

All signals and sources

Why PaisaMaps

Why risk and growth teams use it

Talk to us

Documented signals: Every signal has its source and level, so it can go through model review.
Built for joining: Pincode is the key; CSV, Excel, JSON or API.
Honest granularity: District- and state-level signals say so, and are never presented as pincode measurements.
Fair use built in: Area-level only: nothing about any individual applicant.

Getting started

How teams roll it out

Explore

Read affordability on the free map for your target states.

Pilot

We set up the workspace and an export for one product or region.

Integrate

Join the export to your book on pincode; add an API key for refreshes.

Scale

Higher API limits on Growth and above.

Talk to us

Use cases

The decisions it supports, and how

Use case	How lenders, nbfc & fintech teams use it
Market sizing →	Sizes a loan or payments product by region before launch.
Credit & affordability →	Adds area affordability as a feature next to bureau and customer data.
Territory planning →	Allocates sourcing teams and agents by market strength.

All use cases

Before you buy

Questions we hear

Can this be used for individual credit decisions?

No. It's an area-level signal, the same for everyone in a pincode. Use it alongside your own customer-level data and model governance, not instead of them.

How do we get it into our models?

Export by pincode as CSV, Excel or JSON, or pull it with an API key. Growth and above get higher API limits.

Where do the banking signals come from?

RBI branch and deposit statistics, and PhonePe Pulse for UPI value. The signals page lists each source and level.

Tell us the product and the region

We'll show you the affordability picture and an export you can test in your own model.